A financial data tracing method and system based on blockchain and identification technology

Abstract

The present application relates to the technical field of financial data traceability, and in particular to a financial data traceability method and system based on blockchain and identification technology, the steps of which include: obtaining traceability request information, extracting identification information of the financial data to be traced in the traceability request; determining the time sensitivity coefficient of the traceability request based on the traceability request information; determining the data sensitivity coefficient and data tampering risk coefficient of the financial data to be traced based on the identification information; optimizing the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and controlling the degree of data disclosure in the traceability result according to the data sensitivity coefficient. The present application improves the traceability efficiency and data security of financial data by quantifying the time sensitivity of the traceability request and the degree of data tampering risk of the financial data to be traced, and controlling the degree of data disclosure in a targeted manner based on data sensitivity.

Description

Technical Field

[0001] The present application relates to the technical field of financial data traceability, and in particular to a financial data traceability method and system based on blockchain and identification technology. Background Art

[0002] Financial data is a core element of the financial industry. Financial institutions have accumulated massive amounts of financial data in the process of business operations and digital development. With the explosive growth of application scenarios, financial data has become richer, more complex and diverse, and its characteristics of high value density and great application value have become increasingly prominent.

[0003] Data traceability is the recording of changes and processed information that occur during the entire life cycle of data from its generation to its extinction or conversion. The financial field has strict requirements on the authenticity of data. During the entire life cycle of financial data, the original data may be illegally tampered with. Therefore, during the circulation of financial data, it is necessary to trace and record the original financial data in order to conduct data audits and vulnerability risk compensation, and then prevent data risks in a targeted manner.

[0004] With the widespread application of new-generation information technology in the financial field, the financial data traceability method and blockchain technology are being closely integrated. The existing blockchain-based financial data traceability method ignores the time sensitivity of different traceability requests and the impact of the data tampering risk of the financial data to be traced on the traceability path during the traceability process. Tracing requests with high time sensitivity require higher traceability efficiency, and when the financial data to be traced has a high risk of data tampering, a more complete and detailed traceability process is required. Therefore, how to balance time sensitivity and data tampering risk and specifically control the sensitivity of disclosed data, thereby improving traceability efficiency and data security, is an urgent problem to be solved in the financial field. Summary of the invention

[0005] In order to overcome the defects and shortcomings of the existing technology, the present application provides a financial data traceability method and system based on blockchain and identification technology, which improves the traceability efficiency and data security of financial data by quantifying the time sensitivity of traceability requests and the risk of data tampering of the financial data to be traced, and controlling the degree of data disclosure in the traceability results through data sensitivity.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a financial data tracing method based on blockchain and identification technology, comprising the following steps:

[0008] Obtaining tracing request information, and extracting identification information of the financial data to be traced in the tracing request;

[0009] Determine a time sensitivity coefficient of the tracing request based on the tracing request information;

[0010] Determine the data sensitivity coefficient and data tampering risk coefficient of the financial data to be traced based on the identification information;

[0011] The traceability path is optimized according to the time sensitivity coefficient and the data tampering risk coefficient, and the degree of data disclosure in the traceability result is controlled according to the data sensitivity coefficient.

[0012] Optionally, determining a time sensitivity coefficient of the tracing request includes:

[0013] Obtaining the traceability request information;

[0014] The time sensitivity coefficient of the traceability request is calculated through the traceability request information, and the calculation formula of the time sensitivity coefficient is:

[0015] ;

[0016] In the formula Indicates the maximum allowed time for a traceability request. Indicates the current time. Indicates the time when the traceability request was initiated. Indicates the time sensitivity coefficient of the traceability request.

[0017] Optionally, determining the data sensitivity coefficient includes:

[0018] Acquire the identification information, construct a financial data relationship graph through a graph database, and locate the node position of the financial data to be traced in the financial data relationship graph through the identification information;

[0019] Calculate the data association coefficient and data security coefficient of the financial data to be traced. The calculation formula of the data association coefficient is:

[0020] ;

[0021] In the formula represents the total number of nodes in the financial data relationship graph, Indicates the financial data node to be traced With financial data nodes The shortest distance, Represents the data correlation coefficient of the financial data to be traced;

[0022] The data sensitivity coefficient is calculated by the data association coefficient and the data security coefficient. The calculation formula of the data sensitivity coefficient is:

[0023] ;

[0024] In the formula Represents the data correlation coefficient of the financial data to be traced, Indicates the data security factor of the financial data to be traced. represents the adjustment factor, Represents the data sensitivity coefficient of the financial data to be traced.

[0025] Optionally, calculating the data safety factor includes:

[0026] Obtain the data security level of the financial data to be traced;

[0027] The data security coefficient of the financial data to be traced is calculated by the data security level, and the calculation formula of the data security coefficient is:

[0028] ;

[0029] In the formula Indicates the data security level of the financial data to be traced. Indicates the maximum value of the data security level of financial data. Indicates the minimum value of the data security level of financial data. Indicates the data security factor of the financial data to be traced.

[0030] Optionally, determining the data tampering risk coefficient includes:

[0031] Acquire the identification information, and sequentially acquire historical operation node information of the financial data to be traced through the identification information;

[0032] The operation risk coefficient of the historical operation node is calculated by the historical operation node information, and the calculation formula of the operation risk coefficient is:

[0033] ;

[0034] In the formula Indicates The normal operation times of historical operation nodes, Indicates The number of abnormal operations of historical operation nodes, Indicates Operational risk coefficient of historical operation nodes;

[0035] The data tampering risk coefficient of the financial data to be traced is calculated by the operational risk coefficient. The calculation formula of the data tampering risk coefficient is:

[0036] ;

[0037] In the formula Indicates The operational risk coefficient of historical operation nodes, Indicates the number of historical operation nodes, Indicates the data tampering risk coefficient of the financial data to be traced.

[0038] Optionally, the optimizing the traceability path includes:

[0039] Obtaining the time sensitivity coefficient and the data tampering risk coefficient;

[0040] The traceability efficiency index is calculated by the time sensitivity coefficient and the data tampering risk coefficient. The calculation formula of the traceability efficiency index is:

[0041] ;

[0042] In the formula Indicates the time sensitivity coefficient of the traceability request. Indicates the data tampering risk coefficient of the financial data to be traced. represents the time-sensitive weight, represents the risk weight of data tampering, represents the traceability efficiency index;

[0043] The maximization of the traceability efficiency index is taken as the optimization goal, and the optimal path that meets the optimization goal is found through a heuristic search algorithm, and the optimal path is taken as the traceability path.

[0044] Optionally, the control of the degree of data disclosure in the traceability results includes:

[0045] Obtaining the data sensitivity coefficient;

[0046] When the data sensitivity coefficient is less than the preset data sensitivity threshold, the complete data content is displayed in the traceability result;

[0047] When the data sensitivity coefficient is greater than or equal to a preset data sensitivity threshold, data content having a data security level less than the preset data security level threshold is displayed in the traceability result.

[0048] It should be noted here that the adjustment factor, time-sensitive weight, data tampering risk weight, preset data sensitivity threshold and preset data security level threshold are determined as follows: 5,000 sets of traceability request information are collected, and the traceability efficiency and data disclosure level are distinguished to see whether they meet the traceability requirements. The calculated traceability efficiency index, data sensitivity coefficient and distinction results are simultaneously imported into the fitting software, and the optimal adjustment factor, time-sensitive weight, data tampering risk weight, preset data sensitivity threshold and preset data security level threshold that meet the distinction accuracy of the distinction results are output.

[0049] In the second aspect, the present application provides a financial data tracing system based on blockchain and identification technology, including:

[0050] An information acquisition module, used to acquire tracing request information and extract identification information of the financial data to be traced in the tracing request;

[0051] A first calculation module, configured to determine a time sensitivity coefficient of the tracing request based on the tracing request information;

[0052] A second calculation module, used to determine a data sensitivity coefficient and a data tampering risk coefficient of the financial data to be traced based on the identification information;

[0053] The traceability path optimization module is used to optimize the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and control the degree of data disclosure in the traceability result according to the data sensitivity coefficient.

[0054] In a third aspect, the present application provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a financial data tracing method based on blockchain and identification technology by calling the computer program stored in the memory.

[0055] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enables the computer to execute a financial data tracing method based on blockchain and identification technology.

[0056] Compared with the prior art, this application has the following advantages and beneficial effects:

[0057] This application quantifies the time sensitivity of traceability requests and the data tampering risk of financial data to be traced by calculating the time sensitivity coefficient and the data tampering risk coefficient, and then optimizes the traceability path through the time sensitivity coefficient and the data tampering risk coefficient. At the same time, by quantifying the data sensitivity of the financial data to be traced and specifically controlling the degree of data disclosure in the traceability results, the traceability efficiency and data security of financial data are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0059] Figure 1 This is a schematic diagram of the overall process of a financial data tracing method based on blockchain and identification technology provided in an embodiment of the present application;

[0060] Figure 2This is a flow chart of determining the data tampering risk coefficient in a financial data tracing method based on blockchain and identification technology provided in an embodiment of the present application;

[0061] Figure 3 This is a structural diagram of a financial data tracing system based on blockchain and identification technology provided in an embodiment of the present application;

[0062] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0064] See also Figure 1 , Figure 1 This is a schematic diagram of the overall process of a financial data tracing method based on blockchain and identification technology provided in an embodiment of the present application, which specifically includes the following steps:

[0065] S110: Obtain the traceability request information, and extract the identification information of the financial data to be traced in the traceability request. The identification information is a unique identifier (ID) assigned to the data through identification technology (Identifier Technology), thereby realizing the identification, tracking and management of the data. The unique identification information of the identification technology is combined with the blockchain record to ensure that every link of the data from the source to the terminal can be accurately tracked. The combination of identification technology and blockchain ensures the authenticity, transparency and security of the data in data traceability, and can effectively improve the traceability efficiency.

[0066] S120: Determine a time sensitivity coefficient of the tracing request based on the tracing request information;

[0067] The time sensitivity coefficient directly affects the traceability efficiency and path optimization. A higher time sensitivity coefficient means that the traceability request has a more urgent time requirement. In this case, it is necessary to give priority to faster paths and methods during the traceability process to ensure that the traceability task is completed in the shortest time. The time sensitivity coefficient of the traceability request is determined, including:

[0068] Obtaining the traceability request information;

[0069] The time sensitivity coefficient of the traceability request is calculated through the traceability request information, and the calculation formula of the time sensitivity coefficient is:

[0070] ;

[0071] In the formula Indicates the maximum allowed time for a traceability request. Indicates the current time. Indicates the time when the traceability request was initiated. Indicates the time sensitivity coefficient of the traceability request.

[0072] S130: Determine a data sensitivity coefficient and a data tampering risk coefficient of the financial data to be traced based on the identification information;

[0073] The data sensitivity coefficient measures the sensitivity of the financial data to be traced by comprehensively considering the data correlation degree and data security level of the financial data. In the case of a high data sensitivity coefficient, stricter control should be exercised over the display of data in the traceability results to avoid excessive exposure or improper use of sensitive data. This helps to balance data transparency and privacy protection during the traceability process, thereby ensuring data security while providing effective traceability results. Determine the data sensitivity coefficient, including:

[0074] Acquire the identification information, construct a financial data relationship graph through a graph database, and locate the node position of the financial data to be traced in the financial data relationship graph through the identification information;

[0075] Calculate the data association coefficient and data security coefficient of the financial data to be traced. The calculation formula of the data association coefficient is:

[0076] ;

[0077] In the formula represents the total number of nodes in the financial data relationship graph, Indicates the financial data node to be traced With financial data nodes The shortest distance, Represents the data correlation coefficient of the financial data to be traced;

[0078] The data sensitivity coefficient is calculated by the data association coefficient and the data security coefficient. The calculation formula of the data sensitivity coefficient is:

[0079] ;

[0080] In the formula Represents the data correlation coefficient of the financial data to be traced, Indicates the data security factor of the financial data to be traced. represents the adjustment factor, Indicates the data sensitivity coefficient of the financial data to be traced;

[0081] The data security factor directly affects the degree of data disclosure in the traceability result display. The higher the data security factor, the more stringent restrictions are required on data disclosure to prevent sensitive data leakage. The calculation of the data security factor includes:

[0082] Obtain the data security level of the financial data to be traced, which is obtained through the reference table of typical data classification rules for financial institutions in the "Guidelines for Data Security Classification of Financial Data Security" (JR / T0197-2020);

[0083] The data security coefficient of the financial data to be traced is calculated by the data security level, and the calculation formula of the data security coefficient is:

[0084] ;

[0085] In the formula Indicates the data security level of the financial data to be traced. Indicates the maximum value of the data security level of financial data. Indicates the minimum value of the data security level of financial data. Indicates the data security factor of the financial data to be traced;

[0086] The data tampering risk coefficient measures the possibility of data tampering by evaluating the operational risks of the historical operation nodes of financial data. The operational risk coefficient is determined by the number of normal operations and abnormal operations of each historical operation node. The more abnormal operations there are, the higher the operational risk coefficient of the node is. The overall data tampering risk coefficient is obtained by calculating the operational risk coefficients of the historical operation nodes. The larger the data tampering risk coefficient is, the greater the risk of data tampering during the circulation process is. Therefore, in order to ensure the accuracy and integrity of the data, a more detailed and complete traceability process is required for data with a high data tampering risk coefficient. The authenticity of the data is confirmed through verification of more nodes and links, so as to ensure the consistency and credibility of the data at each node. Please refer to Figure 2 , Figure 2 This is a flow chart of determining the data tampering risk coefficient in a financial data tracing method based on blockchain and identification technology provided in an embodiment of the present application, including:

[0087] Acquire the identification information, and sequentially acquire historical operation node information of the financial data to be traced through the identification information;

[0088] The operation risk coefficient of the historical operation node is calculated by the historical operation node information, and the calculation formula of the operation risk coefficient is:

[0089] ;

[0090] In the formula Indicates The normal operation times of historical operation nodes, Indicates The number of abnormal operations of historical operation nodes, Indicates Operational risk coefficient of historical operation nodes;

[0091] The data tampering risk coefficient of the financial data to be traced is calculated by the operational risk coefficient. The calculation formula of the data tampering risk coefficient is:

[0092] ;

[0093] In the formula Indicates The operational risk coefficient of historical operation nodes, Indicates the number of historical operation nodes, Indicates the data tampering risk coefficient of the financial data to be traced.

[0094] S140: optimizing the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and controlling the degree of data disclosure in the traceability result according to the data sensitivity coefficient;

[0095] The time sensitivity coefficient is used to measure the urgency of the traceability request, while the data tampering risk coefficient reflects the possibility of data tampering. By adjusting the time sensitivity weight and the data tampering risk weight, the timeliness and accuracy requirements in the traceability process are balanced and the traceability path is optimized, including:

[0096] Obtaining the time sensitivity coefficient and the data tampering risk coefficient;

[0097] The traceability efficiency index is calculated by the time sensitivity coefficient and the data tampering risk coefficient. The calculation formula of the traceability efficiency index is:

[0098] ;

[0099] In the formula Indicates the time sensitivity coefficient of the traceability request. Indicates the data tampering risk coefficient of the financial data to be traced. represents the time-sensitive weight, represents the risk weight of data tampering, represents the traceability efficiency index;

[0100] Taking the maximum traceability efficiency index as the optimization goal, finding the optimal path that meets the optimization goal through a heuristic search algorithm, and taking the optimal path as the traceability path, wherein the heuristic search algorithm includes a simulated annealing algorithm (SA), a genetic algorithm (GA) and an ant colony algorithm (ACA);

[0101] In the process of tracing, the data sensitivity coefficient quantifies the sensitivity of the data. When the data sensitivity coefficient is low, the complete data content is displayed to ensure transparency and traceability effect; when the data sensitivity coefficient is high, data disclosure is limited according to the preset threshold, and only data content with a lower security level is displayed, thereby protecting highly sensitive or confidential data from being leaked. The hierarchical control mechanism helps to strike a balance between traceability transparency and data privacy protection, ensuring that the traceability results meet the traceability requirements while reducing the risk of data leakage, and controlling the degree of data disclosure in the traceability results, including:

[0102] Obtaining the data sensitivity coefficient;

[0103] When the data sensitivity coefficient is less than the preset data sensitivity threshold, the complete data content is displayed in the traceability result;

[0104] When the data sensitivity coefficient is greater than or equal to a preset data sensitivity threshold, data content having a data security level less than the preset data security level threshold is displayed in the traceability result.

[0105] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a financial data tracing system based on blockchain and identification technology provided in an embodiment of the present application, including:

[0106] The information acquisition module 210 is used to acquire the traceability request information and extract the identification information of the financial data to be traced in the traceability request;

[0107] A first calculation module 220, configured to determine a time sensitivity coefficient of the tracing request based on the tracing request information;

[0108] A second calculation module 230, configured to determine a data sensitivity coefficient and a data tampering risk coefficient of the financial data to be traced based on the identification information;

[0109] The traceability path optimization module 240 is used to optimize the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and control the degree of data disclosure in the traceability result according to the data sensitivity coefficient.

[0110] In the embodiment of the present application, the first calculation module 220 is used to determine the time sensitivity coefficient of the tracing request based on the tracing request information. The specific steps of determining the time sensitivity coefficient of the tracing request include:

[0111] Obtaining the traceability request information;

[0112] The time sensitivity coefficient of the traceability request is calculated through the traceability request information, and the calculation formula of the time sensitivity coefficient is:

[0113] ;

[0114] In the formula Indicates the maximum allowed time for a traceability request. Indicates the current time. Indicates the time when the traceability request was initiated. Indicates the time sensitivity coefficient of the traceability request.

[0115] In the embodiment of the present application, the second calculation module 230 is used to determine the data sensitivity coefficient and the data tampering risk coefficient of the financial data to be traced based on the identification information. The specific steps of determining the data sensitivity coefficient include:

[0116] Acquire the identification information, construct a financial data relationship graph through a graph database, and locate the node position of the financial data to be traced in the financial data relationship graph through the identification information;

[0117] Calculate the data association coefficient and data security coefficient of the financial data to be traced. The calculation formula of the data association coefficient is:

[0118] ;

[0119] In the formula represents the total number of nodes in the financial data relationship graph, Indicates the financial data node to be traced With financial data nodes The shortest distance, Represents the data correlation coefficient of the financial data to be traced;

[0120] The data sensitivity coefficient is calculated by the data association coefficient and the data security coefficient. The calculation formula of the data sensitivity coefficient is:

[0121] ;

[0122] In the formula Represents the data correlation coefficient of the financial data to be traced, Indicates the data security factor of the financial data to be traced. represents the adjustment factor, Indicates the data sensitivity coefficient of the financial data to be traced;

[0123] The specific steps for calculating the data safety factor include:

[0124] Obtain the data security level of the financial data to be traced;

[0125] The data security coefficient of the financial data to be traced is calculated by the data security level, and the calculation formula of the data security coefficient is:

[0126] ;

[0127] In the formula Indicates the data security level of the financial data to be traced. Indicates the maximum value of the data security level of financial data. Indicates the minimum value of the data security level of financial data. Indicates the data security factor of the financial data to be traced;

[0128] The specific steps to determine the risk factor of data tampering include:

[0129] Acquire the identification information, and sequentially acquire historical operation node information of the financial data to be traced through the identification information;

[0130] The operation risk coefficient of the historical operation node is calculated by the historical operation node information, and the calculation formula of the operation risk coefficient is:

[0131] ;

[0132] In the formula Indicates The normal operation times of historical operation nodes, Indicates The number of abnormal operations of historical operation nodes, Indicates Operational risk coefficient of historical operation nodes;

[0133] The data tampering risk coefficient of the financial data to be traced is calculated by the operational risk coefficient. The calculation formula of the data tampering risk coefficient is:

[0134] ;

[0135] In the formula Indicates The operational risk coefficient of historical operation nodes, Indicates the number of historical operation nodes, Indicates the data tampering risk coefficient of the financial data to be traced.

[0136] In the embodiment of the present application, the traceability path optimization module 240 is used to optimize the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and control the degree of data disclosure in the traceability result according to the data sensitivity coefficient. The specific steps of optimizing the traceability path include:

[0137] Obtaining the time sensitivity coefficient and the data tampering risk coefficient;

[0138] The traceability efficiency index is calculated by the time sensitivity coefficient and the data tampering risk coefficient. The calculation formula of the traceability efficiency index is:

[0139] ;

[0140] In the formula Indicates the time sensitivity coefficient of the traceability request. Indicates the data tampering risk coefficient of the financial data to be traced. represents the time-sensitive weight, represents the risk weight of data tampering, represents the traceability efficiency index;

[0141] Taking the maximum traceability efficiency index as the optimization goal, finding the optimal path that meets the optimization goal through a heuristic search algorithm, and taking the optimal path as the traceability path;

[0142] Specific steps to control the extent of data disclosure in traceability results include:

[0143] Obtaining the data sensitivity coefficient;

[0144] When the data sensitivity coefficient is less than the preset data sensitivity threshold, the complete data content is displayed in the traceability result;

[0145] When the data sensitivity coefficient is greater than or equal to a preset data sensitivity threshold, data content having a data security level less than the preset data security level threshold is displayed in the traceability result.

[0146] The above-mentioned parameters and steps for each unit module to implement corresponding functions in a financial data traceability system based on blockchain and identification technology of the present application can refer to the parameters and steps in the embodiment of a financial data traceability method based on blockchain and identification technology above, and will not be repeated here.

[0147] like Figure 4 As shown, an embodiment of the present invention further provides an electronic device 300, including a memory 320 for storing a computer program 322; and a processor 310 for executing the computer program 322 to implement a financial data tracing method based on blockchain and identification technology as in any of the above embodiments.

[0148] It should be noted that Figure 4 It is a structural diagram of an electronic device 300 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of application of the present invention.

[0149] Specifically, the electronic device 300 may include: at least one processor 310, at least one memory 320, a power supply 330, a communication interface 340, an input / output interface 350, and a communication bus 360. The memory 320 is used to store a computer program 322, which is loaded and executed by the processor 310 to implement the relevant steps in a financial data tracing method based on blockchain and identification technology disclosed in any of the aforementioned embodiments. In addition, the electronic device 300 in the embodiment of the present invention may be specifically an electronic computer.

[0150] In an embodiment of the present invention, a power supply 330 is used to provide a working voltage for each hardware device on the electronic device 300; the communication interface 340 can create a data transmission channel between the electronic device 300 and an external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present invention, and is not specifically limited here; the input and output interface 350 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0151] In addition, the memory 320, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 321, a computer program 322, etc., and the storage method can be temporary storage or permanent storage.

[0152] The operating system 321 is used to manage and control the hardware devices and computer programs on the electronic device 300, and can be Windows Server, NetWare, Unix, Linux, etc. In addition to the computer program 322 that can be used to complete the financial data tracing method based on blockchain and identification technology performed by the electronic device 300 disclosed in any of the aforementioned embodiments, the computer program 322 can further include a computer program 322 that can be used to complete other specific tasks.

[0153] An embodiment of the present invention also provides a computer-readable storage medium for storing a computer program 322. When the computer program 322 is executed by the processor 310, it implements a financial data tracing method based on blockchain and identification technology as in any of the above embodiments.

[0154] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

Claims

1. A financial data tracing method based on blockchain and identification technology, characterized in that: The steps include: Obtaining tracing request information, and extracting identification information of the financial data to be traced in the tracing request; Determine a time sensitivity coefficient of the tracing request based on the tracing request information; Determine the data sensitivity coefficient and data tampering risk coefficient of the financial data to be traced based on the identification information; Optimizing the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and controlling the degree of data disclosure in the traceability result according to the data sensitivity coefficient; The step of determining the time sensitivity coefficient of the traceability request includes: Obtaining the traceability request information; The time sensitivity coefficient of the traceability request is calculated through the traceability request information, and the calculation formula of the time sensitivity coefficient is: ； In the formula Indicates the maximum allowed time for a traceability request. Indicates the current time. Indicates the time when the traceability request was initiated. Indicates the time sensitivity coefficient of the traceability request; Determining the data tampering risk factor includes: Acquire the identification information, and sequentially acquire historical operation node information of the financial data to be traced through the identification information; The operation risk coefficient of the historical operation node is calculated by the historical operation node information, and the calculation formula of the operation risk coefficient is: ； In the formula Indicates The normal operation times of historical operation nodes, Indicates The number of abnormal operations of historical operation nodes, Indicates Operational risk coefficient of historical operation nodes; The data tampering risk coefficient of the financial data to be traced is calculated by the operational risk coefficient. The calculation formula of the data tampering risk coefficient is: ； In the formula Indicates The operational risk coefficient of each historical operation node, Indicates the number of historical operation nodes, Indicates the data tampering risk coefficient of the financial data to be traced; The optimized traceability path includes: Obtaining the time sensitivity coefficient and the data tampering risk coefficient; The traceability efficiency index is calculated by the time sensitivity coefficient and the data tampering risk coefficient. The calculation formula of the traceability efficiency index is: ； In the formula Indicates the time sensitivity coefficient of the traceability request. Indicates the data tampering risk coefficient of the financial data to be traced. represents the time-sensitive weight, represents the risk weight of data tampering, represents the traceability efficiency index; The maximization of the traceability efficiency index is taken as the optimization goal, and the optimal path that meets the optimization goal is found through a heuristic search algorithm, and the optimal path is taken as the traceability path.

2. According to claim 1, a financial data tracing method based on blockchain and identification technology is characterized in that: Determining the data sensitivity coefficient includes: Acquire the identification information, construct a financial data relationship graph through a graph database, and locate the node position of the financial data to be traced in the financial data relationship graph through the identification information; Calculate the data association coefficient and data security coefficient of the financial data to be traced. The calculation formula of the data association coefficient is: ； In the formula represents the total number of nodes in the financial data relationship graph, Indicates the financial data node to be traced With financial data nodes The shortest distance, Represents the data correlation coefficient of the financial data to be traced; The data sensitivity coefficient is calculated by the data association coefficient and the data security coefficient. The calculation formula of the data sensitivity coefficient is: ； In the formula Represents the data correlation coefficient of the financial data to be traced, Indicates the data security factor of the financial data to be traced. represents the adjustment factor, Represents the data sensitivity coefficient of the financial data to be traced.

3. According to claim 2, a financial data tracing method based on blockchain and identification technology is characterized in that: Calculating the data safety factor includes: Obtain the data security level of the financial data to be traced; The data security coefficient of the financial data to be traced is calculated by the data security level, and the calculation formula of the data security coefficient is: ； In the formula Indicates the data security level of the financial data to be traced. Indicates the maximum value of the data security level of financial data. Indicates the minimum value of the data security level of financial data. Indicates the data security factor of the financial data to be traced.

4. According to claim 1, a financial data tracing method based on blockchain and identification technology is characterized in that: The degree of data disclosure in the control traceability results includes: Obtaining the data sensitivity coefficient; When the data sensitivity coefficient is less than the preset data sensitivity threshold, the complete data content is displayed in the traceability result; When the data sensitivity coefficient is greater than or equal to a preset data sensitivity threshold, data content having a data security level less than the preset data security level threshold is displayed in the traceability result.

5. A financial data tracing system based on blockchain and identification technology, which is implemented based on a financial data tracing method based on blockchain and identification technology as described in any one of claims 1 to 4, characterized in that: The system comprises: An information acquisition module, used to acquire tracing request information and extract identification information of the financial data to be traced in the tracing request; A first calculation module, configured to determine a time sensitivity coefficient of the tracing request based on the tracing request information; A second calculation module, used to determine a data sensitivity coefficient and a data tampering risk coefficient of the financial data to be traced based on the identification information; The traceability path optimization module is used to optimize the traceability path according to the time sensitivity coefficient and the data tampering risk coefficient, and control the degree of data disclosure in the traceability result according to the data sensitivity coefficient.

6. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes a financial data tracing method based on blockchain and identification technology as described in any one of claims 1 to 4 by calling the computer program stored in the memory.

7. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes a financial data tracing method based on blockchain and identification technology as described in any one of claims 1 to 4.

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